A FAST MAXIMUM-LIKELIHOOD CLASSIFIER

被引：4
|
作者：
VENKATESWARLU, NB
SINGH, RP
机构：
[1] FREE UNIV BERLIN,INST WELTRAUMWISSENSCH WE4,D-14195 BERLIN,GERMANY
[2] BITS,CTR INFORMAT PROC,PILANI 333031,RAJASTHAN,INDIA
来源：
INTERNATIONAL JOURNAL OF REMOTE SENSING | 1995年 / 16卷 / 02期
关键词：
D O I：
10.1080/01431169508954397
中图分类号：
TP7 [遥感技术];
学科分类号：
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要：
The classification of multiband remote sensing data may require a huge amount of computer time. In the present paper, we discuss a fast maximum likelihood classifier based on the concepts of thresholding, partial sum logic, Winograd's inequality and a linear algebraic theorem. The performance of this classifier has been tested using four sets of remotely-sensed data. The results have been discussed and compared with the original maximum likelihood classifier.
引用
收藏
页码：313 / 320
页数：8
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